Abstract：It is theoretically significant to study on the aging condition assessment of oil-paper insulation based on partial discharge (PD) instead of traditional chemical methods. Moreover, practical application value still exists after refining transformer oil. In this paper, PD of the test samples with different aging degrees was measured after a thermally accelerated aging experiment. Then ten principal component factors were extracted from 29 statistical parameters. The aging condition of oil-paper was characterized utilizing a unit circle. Using the aging radius R as the single objective, an assessment model was established based on a three-layer BP neural network which was trained by genetic algorithm (GA) and Levenberg-Marquardt (LM) algorithm respectively. Finally, the test samples were recognized by the trained GA-BP and LM-BP network. It has been found that GA-BP network has the advantages of higher recognition rates comparing with LM-BP network.
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2010, Vol. 25 
